Switching state-space models: likelihood function, filtering and smoothing

DOI10.1016/S0378-3758(97)00136-5zbMath0944.62085OpenAlexW2094961642MaRDI QIDQ1299533

Alain Monfort, Monica Billio

Publication date: 26 September 2000

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0378-3758(97)00136-5

zbMATH Keywords

smootherimportance samplingstate-space modelswitching modelpartial Kalman filtersequential optimal samplersimulated maximum-likelihood

Mathematics Subject Classification ID

Related Items (5)

Spectral representation and autocovariance structure of Markov switching DSGE models ⋮ Stochastic volatility duration models ⋮ Implied distributions in multiple change point problems ⋮ Estimation of dynamic and ARCH Tobit models ⋮ Bayesian estimation of switching ARMA models

Cites Work

• Analysis of time series subject to changes in regime
• Rational-expectations econometric analysis of changes in regime. An investigation of the term structure of interest rates
• A Markov model for switching regressions
• Dynamic linear models with Markov-switching
• Stochastic volatility in asset prices. Estimation with simulated maximum likelihood
• Simulation estimation of dynamic switching regression and dynamic disequilibrium models - some Monte Carlo results
• Non-Gaussian State-Space Modeling of Nonstationary Time Series
• Finite Element Solutions for Steady State Visco-Plastic Flow
• A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle
• Partial non-Gaussian state space
• STATISTICAL ANALYSIS OF ECONOMIC TIME SERIES VIA MARKOV SWITCHING MODELS
• Testing the term structure of interest rates using a stationary vector autoregression with regime switching

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